Assessing Long-Term Exposure in the California Teachers Study

Kessler (2011) provided a valuable update on the current state of research and regulatory policy concerning nanomaterials. However, the article could give the misleading impression that the precautionary principle constitutes a straightforward guideline for improving public policy in this area. Instead, the precautionary principle provides only a general framework that must be specified before one can adequately assess its implications for policy. 
 
Near the beginning of the article, Kessler (2011) quoted Alexis Baden-Mayer, who worried, 
 
[I]n our regulation of food and consumer products, we don’t implement the precautionary principle. Things go to market before we know whether or not they’re really safe for human beings over the long term. 
 
Kessler (2011) concluded with a quotation from Michael Hansen: 
 
I think we need to take a precautionary approach because we’ve learned the hard way over and over and over again. You’d think we would learn. 
 
By framing the issues in this way, Kessler (2011) intimated that the precautionary principle could serve as a valuable guide for future research and policy making. However, without further specification, the principle provides only a rough outlook or orientation rather than a specific regulatory plan of action; its merits cannot be clearly evaluated unless a number of further questions are answered. 
 
A number of scholars have attempted to clarify how various formulations of the precautionary principle relate to one another. There are at least three important features that vary in different accounts of the principle: a) the threats that ought to be addressed; b) the amount and kinds of knowledge necessary to justify precautionary measures; and c) the specific precautionary measures that ought to be taken (Elliott 2010; Manson 2002; Sandin 1999). All three issues require further discussion in the case of nanomaterial research and regulation. 
 
Regarding threats, one of the most crucial issues is whether it is sufficient to show that nanoparticles are safe for humans or whether they must also be shown to be safe for the environment—and, if so, what environmental impacts must be tested. Andrew Maynard hinted at this issue: 
 
I think there is a greater chance that we’re going to see long-term environmental impacts from these materials than we are going to see short-term consumer impacts. (Kessler 2011) 
 
Given the vast array of nanoparticles under consideration, it seems doubtful that they could all be thoroughly tested for a wide range of environmental effects before allowing their use. 
 
This raises the question of how much evidence should be demanded before approving particular sorts of nanoparticles. A number of questions are relevant here, some of which are touched on by Kessler (2011): What kinds of screening studies should be required? When should in vivo studies be required? What structural or functional changes to a nanoparticle (e.g., size, crystal structure, manufacturing process) should trigger new toxicity studies? Should by-products of the production process also be studied in order to declare a nanoparticle safe (Templeton et al. 2006)? What steps must be taken to ensure that multiple manufacturing batches of the same nanoparticle result in products with the same toxicity profile? Does it matter what kinds of consumer products the nanoparticles are used for? 
 
Finally, although many proponents and opponents of the precautionary principle treat the precautionary principle as if it requires bans on potential threats until they are shown to be safe, a range of other positions are also available on this issue. Three options include a) insisting that government agencies be notified when products contain particular nanoparticles; b) demanding labeling; or c) taking steps to minimize human or environmental exposure to nanoparticles until they have received further testing. Kessler (2011) highlighted our present failure to achieve some of these minimal steps. 
 
These considerations do not by themselves count as sufficient reasons for rejecting the precautionary principle, but they do show that the decision to adopt it is the start of a complicated conversation rather than a straightforward choice about how to regulate nanomaterials.


Nanomaterials and the Precautionary Principle
doi: 10.1289/ehp.1103687 Kessler (2011) provided a valuable update on the current state of research and regulatory pol icy concerning nano materials. However, the article could give the mis leading impression that the precautionary principle constitutes a straightforward guideline for improving public policy in this area. Instead, the precautionary principle provides only a general framework that must be specified before one can ade quately assess its implications for policy.
Near the beginning of the article, Kessler (2011) quoted Alexis BadenMayer, who worried, [I]n our regulation of food and consumer prod ucts, we don't implement the precautionary principle. Things go to market before we know whether or not they're really safe for human beings over the long term.
Kessler (2011) concluded with a quotation from Michael Hansen: I think we need to take a precautionary approach because we've learned the hard way over and over and over again. You'd think we would learn.
By framing the issues in this way, Kessler (2011) intimated that the precautionary prin ciple could serve as a valuable guide for future research and policy making. However, with out further specification, the principle provides only a rough outlook or orientation rather than a specific regulatory plan of action; its merits cannot be clearly evaluated unless a number of further questions are answered.
A number of scholars have attempted to clar ify how various formulations of the precaution ary principle relate to one another. There are at least three important features that vary in differ ent accounts of the principle: a) the threats that ought to be addressed; b) the amount and kinds of knowledge necessary to justify precaution ary measures; and c) the specific precautionary measures that ought to be taken (Elliott 2010;Manson 2002;Sandin 1999). All three issues require further discussion in the case of nano material research and regulation.
Regarding threats, one of the most crucial issues is whether it is sufficient to show that nano particles are safe for humans or whether they must also be shown to be safe for the environment-and, if so, what environmental impacts must be tested. Andrew Maynard hinted at this issue: I think there is a greater chance that we're going to see longterm environmental impacts from these materials than we are going to see shortterm consumer impacts. (Kessler 2011) Given the vast array of nano particles under consideration, it seems doubtful that they could all be thoroughly tested for a wide range of environmental effects before allow ing their use.
This raises the question of how much evi dence should be demanded before approving particular sorts of nano particles. A number of questions are relevant here, some of which are touched on by Kessler (2011): What kinds of screening studies should be required? When should in vivo studies be required? What structural or functional changes to a nano particle (e.g., size, crystal structure, manufacturing process) should trigger new toxicity studies? Should byproducts of the production process also be studied in order to declare a nano particle safe (Templeton et al. 2006)? What steps must be taken to ensure that multiple manufacturing batches of the same nano particle result in products with the same toxicity profile? Does it matter what kinds of consumer products the nano particles are used for?
Finally, although many proponents and opponents of the precautionary principle treat the precautionary principle as if it requires bans on potential threats until they are shown to be safe, a range of other positions are also available on this issue. Three options include a) insisting that government agencies be noti fied when products contain particular nano particles; b) demanding labeling; or c) taking steps to minimize human or environmen tal exposure to nano particles until they have received further testing. Kessler (2011) high lighted our present failure to achieve some of these minimal steps.
These considerations do not by them selves count as sufficient reasons for reject ing the precautionary principle, but they do show that the decision to adopt it is the start of a complicated conversation rather than a straightforward choice about how to regulate nano materials. We read with interest the the article by Bouchard et al. (2011) on the effect of manga nese in drinking water on children's IQ (intel ligence quotient). In this crosssectional study, the authors examined IQ scores in relation to manganese exposure using four exposure metrics: a) concentration of manganese in tap water; b) concentration of manganese in hair samples; c) estimate of manganese intake from water consumption; and e) estimate of man ganese intake from diet consumption.
One key finding from the study of Bouchard et al. (2011) is that a higher concen tration of manganese in tap water was signifi cantly associated with lower IQ. Compared with the other three exposure metrics used in the study, the concentration of manganese in water followed an almost perfect doseresponse relationship with children's IQ, and it was shown to be a better predictor of lower IQ than the exposure metrics. We found this surprising for three reasons. First, in their analysis of the association between concen tration of manganese in tap water and IQ, Bouchard et al. included the entire study pop ulation (n = 362). We consider this inappro priate because 33% of the study participants (n = 121) did not drink tap water at home. Thus, these 121 children may have experi enced much lower exposure to manganese from tap water than the remaining children in the study. Second, if we consider the highest quintile of watermanganese concentration (median, 216 μg/L), the estimated manganese intake from water would be ≤ 0.43 mg/day for half of the children in this exposure group, assuming a daily water intake of 2 L. Even at this level, the intake of manganese from water was still far below the daily intake recom mended by the Institute of Medicine (2001): children 1-3 years of age (1.2 mg/day) and children 4-13 years of age (1.5-1.9 mg/day). Third, Bouchard et al. reported that the chil dren's manganese intake from food was more than two orders of magnitude compared to Environmental Health Perspectives • volume 119 | number 6 | June 2011

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Correspondence the amount ingested from water. This sug gests that if elevated manganese was causally related to lower IQ, the decrease in IQ was more likely due to the intake of manganese from both water and food sources than from water alone. While one can postulate differ ences in bio availability between manganese in food and in water, these would need to be considerable to result in equal or greater uptake from water than from food.
The utility of hair as a biomarker for human exposure to manganese has yet not been established [Agency for Toxic Substances and Disease Registry (ATSDR) 2001]. There is still a lack of standard pro cedure for collection of hair samples as well as insufficient evidence to demon strate the effect of washing hair on analytical results (ATSDR 2001). Bouchard et al. (2011) excluded children with dyed hair, but it would be interesting to also distinguish chil dren with natural hair of different colors in the analysis, because levels of manganese in hair can vary by natural colors of hair. Bouchard et al. (2011) generated an interesting hypothesis on neuro toxicity of water manganese in children at a level that is currently considered to have no adverse effect (World Health Organization 2008), but we believe more studies will be needed to confirm their findings. To better characterize human exposure to manganese from water, it is important for future studies to quan tify bio availability of manganese from water and from food sources. In addition, employ ing a prospective study design and control ling for all possible risk factors-including overall nutritional status-will be critical. Additionally, comparing hair with other bio markers of manganese exposure would be another area to explore for future studies.
The authors declare they have no actual or potential competing financial interests. Chen and Copes raise some interesting issues regarding our article (Bouchard et al. 2011). In our study we investigated the change in IQ scores with respect to different exposure metrics for manganese. One of these metrics was home tap water manganese concentration, which was strongly associated with IQ deficits. Chen and Copes indicate that they consider it inappropri ate to include in this analysis children who did not drink tap water at home. Second, they note that even for children in the highest quintile of water manganese concentration, the intake of manganese from water ingestion is below the recom mended dietary manganese intake (Institute of Medicine 2001). In response to their first point, it is important to consider that children who do not drink tap water are still exposed through the consumption of many foods and drinks prepared with tap water. In addition, and perhaps most important, chil dren might be exposed by inhalation of aero sols containing manganese when showering (Elsner and Spangler 2005). If this represents a significant source of exposure, which is unclear (Aschner 2006;Spangler and Elsner 2006), inhalation of aerosols could be responsible for inducing neuro toxic effects. Indeed, inhaled manganese is delivered to the brain much more efficiently than ingested manganese, because it bypasses normal homeo static mechanisms.

Hong Chen Ray Copes
Third, Chen and Copes make the point that because dietary intake of manganese intake is much higher than the amount ingested from water, the decrease in IQ is more likely due to intake of manganese from water and food sources collectively, rather than from water alone. The intake of man ganese from water consumption was indeed very small compared with dietary intake (medians, 8 and 2,335 μg/kg/month, respec tively), but we found no evidence that dietary manganese is related to cognitive abilities. As we reported in our article (Bouchard et al. 2011), dietary manganese intake, assessed with a food frequency questionnaire, was not associated with IQ and did change the point estimates for water manganese concentration when included in the regression model.
We believe that the interpretations that assimilate manganese present in water to dietary manganese have had the effect of dismissing the potential risks of this source of exposure, thus slowing research into this question. Little is known about the absorption and retention of manganese from food versus water, or about inhalation of aerosols in showers. Although more research is necessary to understand the mechanisms by which manganese present in water might be neuro toxic for children, we believe that our findings offer strong support for this hypothesis. Because manganese levels asso ciated with significant cognitive deficits in our study are common in ground water, this prob lem could have a great public health impor tance. For instance, 11% of domestic wells have manganese concentrations > 140 μg/L in the United States (U.S. Geological Survey 2009). We agree that additional studies, ideally with a prospective design, are necessary.
Finally, a valid biomarker of manga nese exposure would greatly advance our understanding of this metal's toxic effects. We used hair, notably because its collection is much less invasive than blood sampling. Chen and Copes rightly point out the limi tations of hair as a biomarker, and research should explore new biomarkers. For instance, in a small study, saliva manganese levels were significantly higher in welders than in non exposed subjects, and levels increased in welders with the more years of exposure (Wang et al. 2008). Also in that study, saliva manganese concentrations correlated with serum concentrations. Saliva is less invasive to collect than blood and less prone to exter nal contamination than hair; thus, it might be a useful biomarker.
The author declares that she has no actual or potential competing financial interests.

Department of Environmental and
Occupational Health University of Montreal Montreal, Québec, Canada Email: maryse.bouchard@umontreal.ca

Erratum: Assessing Long-Term Exposure in the California Teachers Study
In an article published in Environmental Health Perspectives , we analyzed the relation ships of longterm exposure to fine particulate matter (≤ 2.5 μm in aerodynamic diameter; PM 2.5 ) and its components with mortality in a cohort of > 100,000 active and retired female professionals participating in the California Teachers Study (CTS) cohort. We used a Cox proportional hazards model in which pollution exposure was measured as a continuous variable over the study period. Monthly average pollutant concentrations were obtained for each participant from measurements at the nearest PM 2.5 moni tor within either 8 or 30 km of her geocoded resi dential address. Each participant was assigned a single exposure value over the followup period, defined as the average pollutant concentration from the begin ning of the observation period (1 June 2002) to the woman's date of death, loss to followup, or study termination (31 July 2007). Thus, exposure assignment was dependent on the duration of followup for each participant.
In our article , we reported associations of mortality from all causes, cardio pulmonary disease, and ischemic heart disease (IHD) with PM 2.5 mass and several of its components. However, the estimated hazard ratios (HRs) were generally higher than those reported from previous cohort studies (Dockery et al. 1993;Eftim et al. 2008;Krewski et al. 2009;Laden et al. 2006;Pope et al. 1995). Part of this difference was likely due to the nature of the exposure assignment. Most previous cohort studies have assigned the same exposure period to all study subjects, regardless of when deaths occurred. Thus, estimated exposures for some study participants in several studies occurred after their deaths. In addition, exposures have usually been assigned to participants based on their residential address at enrollment only, without taking into account exposure changes that may have occurred throughout the study period or when par ticipants relocated. Finally, many previous studies measured exposure for only a subset of the years during which the cohort was followed.
In an effort to reduce these aspects of exposure mis classifi ca tion, we estimated exposures beginning prior to the cohort followup period, continuing to the end of the study or until the participant died or relocated out of state, incorporating updated exposure assignments when the subjects moved. Importantly, measured concentrations of several pollutants in California declined substantially from 2002 through 2007; annual average PM 2.5 , organic carbon (OC), and nitrates decreased by around 30% each. These marked decreases in ambient PM 2.5 concentrations resulted in lower average exposure estimates for cohort members who survived to the end of our study. Thus, the exposure assigned to a par ticipant who died at time t would tend to be greater for events occur ring early in the observation period, compared with the longterm average exposures of the participants who comprised the remainder of the risk set (i.e., those who were still part of the cohort study at time t and who subsequently experienced lower ambient pollution levels).
We have reanalyzed the CTS data using timedependent pollu tion metrics-in which the exposure estimates for everyone remaining alive in the risk set were recalculated at the time of each death-in order to compare their average exposures up to that time with that of the individual who had died. In this way, decedents and survi vors comprising the risk set had similar periods of pollution expo sure, without subsequent pollution trends influencing the surviving women's exposure estimates.
As in our previous study , we restricted the sample in this reanalysis to women living within 30 km of one of eight fixedsite monitors in the U.S. Environmental Protection Agency's Speciation Trend Network (STN), resulting in a study population of almost 44,000 women. Residential addresses from study enrollment forward were geo coded and linked with monthly pollutant averages at the nearest STN monitor to generate estimates of longterm exposure. We also used the same set of individual and ecological covariates in a Cox proportional hazards model as was used in the original study. Pollutants entered separately into the model included PM 2.5 mass, elemental carbon (EC), OC, sulfate, nitrate, iron, potassium, silicon, and zinc. We used data on primary cause of death from August 2002 through July 2007 to examine the relationships between pollutants and mortality from all causes and cardiopulmonary, pulmonary, and IHDs.
The results are summarized in Erratum Table 1, scaled to the inter quartile range (IQR) for each pollutant. HRs were significantly attenuated from our previous results. No associations were observed between allcause mortality and PM 2.5 or its components. For cardio pulmonary mortality, we observed significant associations for PM 2.5 mass, nitrate, sulfate, and silicon, with more modest associations for zinc. PM 2.5 mass and all of its components were associated with mor tality from IHD, whereas none of the pollutants was associated with Erratum Table 1. Association between mortality outcomes and PM 2.5 and its components using a 30-km buffer (n = 43,220).